S4 Data - by Renjie Wang (1986553)

“…Pn decreased significantly across treatments, with D1CK>D2>D3. …”

S7 Data - by Renjie Wang (1986553)

“…Pn decreased significantly across treatments, with D1CK>D2>D3. …”

Time series of validations on buses using <i>smart-cards</i> during the COVID-19 pandemic period in 2020. by Jorge L. B. Araújo (20324246)

Circular plot of the forward (ForMR) and reverse (RevMR) MR analyses with inverse variance weighted (IVW) estimates from the 1^st metabolite set (metabolite ratios). by Ozvan Bocher (13813416)

Circular plot of the forward (ForMR) and reverse (RevMR) MR analyses with inverse variance weighted (IVW) estimates from the 1^st metabolite set (absolute metabolite valu... by Ozvan Bocher (13813416)

Alignment of the Taxane binding pocket sequences. by Jacopo Zattoni (21702634)

“…We found that the amoeba’s mitotic tubulins show a significant number of changes that are expected to decrease their affinity for tubulin-targeting compounds. …”

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Time course of IRF1 and IFITM3 RNA and protein expression across conditions. by Tyron Chang (9922533)

Metric correlation matrix. by Chao Song (379006)

Mean scores and 95% CI of mental health symptoms, COVID-19 admissions and effect size during follow-up. by A. H. Ayesha Lavell (16734002)

Accuracy test results. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Experiment environment and parameter. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Test results for NME and FR. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

DARTS algorithm process. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Comparison result of memory usage. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

LKA model structure. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Test results on different datasets. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Comparison result of memory usage. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

Residual configuration. by Yuxuan Ji (13991895)

“…In the testing on the ImageNet dataset, the classification accuracy of the research model is 94.01, the search parameter required is only 4.8MB, the search time is shortened to 0.5d, and the minimum number of floating-point operations is 3.7G, significantly better than other mainstream algorithms. …”

A schematic view of ACS. by Mohammed Qasim Shaheen (21417079)

“…In addition, the results examine a significant reduction in CO₂ emissions by 1.58 kg/hr. …”